Geovisualization

The following maps provide a good example for figure-ground relationship, which refers to a map's perceptual organization of the figure (i.e. the features of the map) with the users and the ground (i.e. the background of the map). The common technique to accentuate figure-ground relationship is to have high visual contrast between the features and the background, either by making the background much darker and the feature much lighter (as in the first map) or making the background much lighter and the features much darker (as in the second map).

The two maps belows depict the number of internet users and the rate of internet usage as percentage of population by countries. The first map is a dual aixis map, which has two visual variables overlay on one another. In the case of this map, the color represents the rate of internet usage and the circle size represents the number of internet users. The second map is a dual encoded circle map, which encodes two visual variables simultenously within the circles. The color of the circles represents the rate of internet usage, and the size of the circles represents the number of internet users. The dual encoded circle map commuciates the information more efficiently than the dual aixis map because it is easier to read and less intimidating. Nonetheless, the audience still has to take some time to decode the map. A better alternative presentation might be just present one variable with the map and another variable with an inset table (i.e. top 10 and bottom 10 countries). ...

The following graphs show three different ways to depict temporal data: a line graph, a connected scatterplot, and a Ganntt bar graph. A line graph, with a timeline on the x-axis, allows the audience to quickly detect temporal patterns. However, when two phenomena are shown in the same graph, the audience might get confused that those phenomena have the same unit. Thus, chart makers have to emphasize the right-side x-axis to make sure audience understand that those phenomena have different units. The connected scatterplot is the one in which disadvatanges might outwieght advantages. Ususally a scatterplot is to allow the audience to quickly tell whether there is a positive or negative relationship, but connect the dots to emphasize the time dimension might even obscure the ability of the audience to see the relationship. Indeed, from the line graph, the audience can see both the increasing trend and the positive correlation between pitchers and stikeout, whereas it is hard to detect ...

This quadrant plot shows that most counties are in the bottom left and the upper right quadrants, indicating that there is a positive relationship between child poverty rate and young adult's low level of education. Counties in the bottom left quadrant are those in which child poverty rate and young adults having less than high school are below average, whereas countries in the top right quadrant are those above average. Small number of counties are in the upper left quadrant and the lower right quadrant in which the relationship between child poverty rate and young adult education are not as expected. Counties in the upper left quadrant have percentage of young adults having less than high school higher than average, despite having child poverty rate lower than average. Counties in the lower right quadrant, on the other hand, have child poverty rate higher than average, yet still have percentage of young adult with education less than high school lower than ...

The top figure is a scatterplot, while the bottom figure is a quadrant chart. In general, quadrant chart is more effective because its has average lines that divide the phenomena into those above average and those below average. Thus, audience can more effortlessly tell which phenomena are in the norm, which phenomena are out of norm, and in what direction.

The dot chart and the waterfall chart has both pros and cons in showing the COVID cases in Illinois counties. The dot chart allows audience to quickly know which county has the most cases, which county has the least, and which county has more case than which county. However, audience has to think a bit if they want to know how many case of the top 10 counties. This is where the waterfall chart might be better because its stacked bars allows audience to quickly understand the cumulative number of cases.

The box plot shows that Staten Island, on average, has higher rate of refuse per person than other boroughs. Its median community district has 78.12 lbs of refuse per person. On the other hand, Manhatthan has the lowest rate of refuse per person among the five boroughs in New York City. Its median community district has only 49.6 lbs of refuse per person.